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MAT510
Preview: MAT510 : Business Statistics
Course Guide
Prerequisites
Course Description
This course explores how business leaders can apply statistical thinking to improving business
processes and performance. The course presents concepts related to statistical thinking within a
business environment, statistical tools and techniques, and formalized statistical methods.
Instructional Materials
Required Resources
David F. Groebner. 2018. Business Statistics: A Decision-Making Approach. MAT510 Pearson 10th
edition textbook available at https://www.strayerbookstore.com
Excel Statistics Essential Training: 1
Microsoft Office365.
A subscription to Office365 is provided to all students. You will use Excel, PowerPoint, and
Word to complete statistics training and other activities in this course.
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information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Course Learning Outcomes
1
Apply strategies that are informed by the principles of statistical thinking and
data-driven decision making to enhance business process performance.
2
Determine solutions for complex problems using statistical tools and
mathematical thinking as a foundation for data-driven decision making.
3
Develop recommendations to improve business processes using statistical
tools and analysis.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Weekly Course Schedule
Week 1 - To Do List
Learn: Read Chapter 1 in Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 1 PowerPoint.
Learn: View Section 1 from Excel Statistics Essential Training: 1.
Discuss: Introduce yourself and complete the discussion, Data Collection Techniques.
Activity: Complete the Data Collection Practice activity.
Week 2 - To Do List
Learn: Read Chapter 2 in Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 2 PowerPoint.
View Section 2 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Data Description Using Graphs and Tables.
Activity: Complete the activity, Scatter Diagram Analysis.
WWeekeek 33 -- TToo DoDo ListList
Learn: Read Chapter 3
in Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 3 PowerPoint.
Learn: View Sections 3 and 4 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Measures of Central Tendency and Variation.
Activity: Complete the activity, Data Description Methods.
Week 4 - To Do List
Learn: Read Chapter 5
in Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 5 PowerPoint.
Learn: View Sections 5 and 6 from Excel Statistics Essential Training: 1.
Assignment: Complete Case Study: Transforming Data Into Information.
Week 5 - To Do List
Learn: Read Chapter 6 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 6 PowerPoint.
Learn: View Section 7 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Discrete and Continuous Probability.
Quiz: Complete the Week 5 Midterm Exam.
Week 6 - To Do List
Learn: Read Chapter 7 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 7 PowerPoint.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Week 6 - To Do List
Learn: View Sections 8 and 9 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Sampling Distributions.
Activity: Complete the activity, Sampling Distribution.
Week 7 - To Do List
Learn: Read Chapter 9 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 9 PowerPoint.
Learn: View Sections 10, 11, and 12 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Application of Hypothesis Testing.
Activity: Complete the activity, Hypothesis Testing.
Week 8 - To Do List
Learn: Read Chapter 14 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 14 PowerPoint.
Learn: Review the Strayer Writing Standards (SWS) - PowerPoint slideshow.
Learn: Review PowerPoint 2019 Essential Training.
Learn: View Section 20 from Excel Statistics Essential Training: 1.
Assignment: Complete the assignment, Case Study: Statistical Inference.
Week 9 - To Do List
Learn: Read Chapter 14 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 14 PowerPoint.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Week 9 - To Do List
Learn: View Section 21 from Excel Statistics Essential Training: 1.
Discuss: Complete the discussion, Application of Linear Regression and Correlations.
Activity: Complete the activity, Linear Regression Analysis.
Week 10 - To Do List
Learn: Read Chapter 15 from Business
Statistics:
A
Decision-Making
Approach.
Learn: Review the Chapter 15 PowerPoint.
Discuss: Complete the discussion, Multiple Regression Analysis.
Assignment: Complete the assignment, Multiple Regression Analysis.
Week 11 - To Do List
Discuss: Complete the discussion, Reflection.
Exam: Complete the Week 11 Final Exam.
Grading Scale
Participation
Total Points % of Grade
Discussion Participation
225 22.5%
Assignment
Total Points % of Grade
Activity: Data Collection Practice
45 4.5%
Activity: Scatter Diagram Analysis
45 4.5%
Activity: Data Description Methods
45 4.5%
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information and may not be c
opied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Assignment
Total Points % of Grade
Week 4 Assignment - Case Study: Transforming
Data Into Information
110 11%
Week 5 Midterm Exam
100 10%
Activity: Sampling Distribution
45 4.5%
Activity: Hypothesis Testing
45 4.5%
Week 8 Assignment - Case Study: Statistical
Inference
150 15%
Activity: Linear Regression Analysis
45 4.5%
Activity: Multiple Regression Analysis
45 4.5%
Week 11 Final Exam
100 10%
Totals 1000 100%
Final Course Grade
Points Percentage Grade
900 - 1000 90% - 100%
A
800 - 899 80% - 89%
B
700 - 799 70% - 79%
C
600 - 699 60% - 69%
D
0 - 599 59% and below
F
Unique Course Features
Grading Scale Notation
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Please consult the University Catalog and your academic advisor to determine the final grade needed
in this class to satisfy your specific degree conferral requirements.
Academic Integrity
Please be sure to review the entire Academic Integrity Policy in the Student Handbook before
submitting anything in this course. In order to enforce its Academic Integrity Policy, the University
reserves the right to review any work (draft or otherwise) or exam submitted by a student during his or
her entire academic career at Strayer.
Assignments
Activity: Data Collection Practice
Summary
Click the linked activity title to access this activity.
Text
A maker of energy drinks is considering abandoning can containers and going exclusively to bottles
because the sales manager believes customers prefer drinking from bottles. However, the vice
president in charge of marketing is not convinced the sales manager is correct. Investigate this issue
using statistical analysis.
1. Explain which data collection method you would use and what procedures you would follow to
apply this method to this situation.
2. Propose which level of data measurement applies to the data collected. Justify your answer.
3. Determine whether the data is qualitative or quantitative.
4. Submit your work in a Word document.
Scoring Guide
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Explain which data collection method you would use and what procedures you would follow to
apply this method to this situation. 34 %
Unacceptable (Below
70%)
Does not explain
which data collection
method you would
use and what
procedures you would
follow to apply this
method to this
situation.
Needs Improvement (70-
79%)
Identifies a data
collection method and
steps to follow in this
situation.
Competent (80-89%)
Describes a data
collection method to
use and lists the steps
to apply this method
to this situation.
Exemplary (90-100%)
Explains which data
collection method you
would use and what
procedures you would
follow to apply this
method to this
situation.
Propose which level of data measurement applies to the data collected. 33 %
Unacceptable (Below
70%)
Does not propose
which level of data
measurement applies
to the data collected.
Needs Improvement (70-
79%)
Presents the wrong
level of data
measurement applied
to the data collected.
Competent (80-89%)
Recommends,
incompletely, the level
of data measurement
applied to the data
collected.
Exemplary (90-100%)
Proposes which level
of data measurement
applies to the data
collected.
Determine whether the data is qualitative or quantitative. 33 %
Unacceptable (Below
70%)
Does not determine
the difference
between qualitative
and quantitative data.
Needs Improvement (70
79%)
Describes the
difference between
qualitative and
quantitative data.
-
Competent (80-89%)
Distinguishes
between qualitative
and quantitative data,
but does not apply it
to the case.
Exemplary (90-100%)
Determines whether
the data is qualitative
or quantitative.
Activity: Scatter Diagram Analysis
Summary
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information and may not be c
opied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Click the linked activity title to access this activity.
Text
The regional sales manager for American Toys, Inc., recently collected data on weekly sales (in
dollars) for the 15 stores in his region. He also collected data on the number of salesclerk work
hours during the week for each of the stores. The data are as follows:
Store Sales Hours
1 23,300 120
2 25,600 135
3 19,200 96
4 10,211 102
5 19,330 240
6 35,789 190
7 12,540 108
8 43,150 234
9 27,886 140
10 54,156 300
11 34,080 254
12 25,900 180
13 36,400 270
14 25,760 175
15 31,500 256
To complete this activity:
1. Use Excel to develop a scatter diagram of the data, including dependent and independent
variables on their correct axis.
2. In a Word document, analyze the relationship between sales and number of clerk hours worked.
3. Conclude, based on the scatter diagram, what adjustments the sales manager might make to
address the relationship between sales and number of clerk hours worked.
4. Submit your work in a Word document with your Excel file attached.
Scoring Guide
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Develop a scatter diagram of the data, including dependent and independent variables on their correct
axis. 34 %
Unacceptable (Below
70%)
Does not develop a
scatter diagram of the
data, including
dependent and
independent variables
on their correct axis.
Needs Improvement (70-
79%)
Develops a scatter
diagram of the data
with incorrect
selection of the
dependent and
independent
variables.
Competent (80-89%)
Develops a scatter
diagram of the data
with correct selection
of variables, but plots
them on the incorrect
axis.
Exemplary (90-100%)
Develops a scatter
diagram of the data,
including dependent
and independent
variables on their
correct axis.
Analyze the relationship between sales and number of clerk hours worked. 33 %
Unacceptable (Below
70%)
Does not analyze the
relationship between
sales and number of
clerk hours worked.
Needs Improvement (70-
79%)
Identifies a
relationship between
sales and number of
clerk hours worked,
but with incorrect
calculations.
Competent (80-89%)
Describes the
relationship between
sales and number of
clerk hours worked.
Exemplary (90-100%)
Analyzes the
relationship between
sales and number of
clerk hours worked.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Conclude, based on the scatter diagram, what actions, if any, the sales manager might take with
respect to the relationship between sales and number of clerk hours worked. 33 %
Unacceptable (Below
70%)
Does not conclude
what actions the sales
manager might take
with respect to the
relationship between
sales and number of
clerk hours worked.
Needs Improvement (70-
79%)
States facts, based on
the scatter diagram,
about the relationship
of sales and number
of clerk hours.
Competent (80-89%)
Concludes but with an
error, based on the
scatter diagram, what
actions, if any, the
sales manager might
take with respect to
the relationship
between sales and
number of clerk hours
worked.
Exemplary (90-100%)
Conclude, based on
the scatter diagram,
what actions, if any,
the sales manager
might take with
respect to the
relationship between
sales and number of
clerk hours worked.
Activity: Data Description Methods
Summary
Click the linked activity title to access this activity.
Text
Japolli Bakery makes a variety of bread types that it sells to supermarket chains in the area. One of
the problems is that the number of loaves of each type of bread sold each day by the chain stores
varies considerably, making it difficult to know how many loaves to bake. A sample of daily demand
data is contained in the file, Japolli Bakery.
1. Develop a frequency distribution for each bread type using appropriate intervals.
2. Select which bread type has the greatest and lowest relative variability.
3. Assuming that these sample data are representative of demand during the year, determine how
many loaves of each type of bread should be made such that demand would be met on at least
75% of the days during the year.
4. Submit your work in a Word document and attach your Excel file.
Scoring Guide
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Develop a frequency distribution for each bread type using appropriate intervals. 34 %
Unacceptable (Below
70%)
Does not develop a
frequency distribution
for each bread type
using appropriate
intervals.
Needs Improvement (70-
79%)
Develops a frequency
distribution for each
bread type using
incorrect intervals.
Competent (80-89%)
Develops a frequency
distribution for each
bread type with some
errors in the intervals.
Exemplary (90-100%)
Develops a frequency
distribution for each
bread type using
appropriate intervals.
Select which bread type has the greatest and lowest relative variability. 33 %
Unacceptable (Below
70%)
Does not select which
bread type has the
greatest and lowest
relative variability.
Needs Improvement (70-
79%)
Selects the bread type
with the greatest and
lowest relative
variability using the
incorrect formula.
Competent (80-89%)
Selects the bread type
with the greatest and
lowest relative
variability using the
incorrect standard
deviation.
Exemplary (90-100%)
Selects which bread
type has the greatest
and lowest relative
variability.
Determine how many loaves of each type of bread should be made such that demand would be met on
at least 75% of the days during the year. 33 %
Unacceptable (Below
70%)
Does not determine
how many loaves of
each type of bread
should be made such
that demand would be
met on at least 75% of
the days during the
year.
Needs Improvement (70-
79%)
Calculates,
incorrectly, how many
loaves of each type of
bread should be made
such that demand
would be met on at
least 75% of the days
during the year.
Competent (80-89%)
Determines how
many loaves of each
type of bread should
be made such that
demand would be met
on at least 75% of the
days, but for less than
the year timeframe.
Exemplary (90-100%)
Determines how
many loaves of each
type of bread should
be made such that
demand would be met
on at least 75% of the
days during the year.
Week 4 Assignment - Case Study: Transforming Data Into Information
Summary
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information and may not be c
opied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Click the linked activity title to access this assignment.
Text
Overview
You are a supervisor at Regional Call Center's Washington, DC, facility. Regional provides contract
call center services for a number of companies, including banks and major retail companies. You
have been with the company for slightly more than seven years, having joined Regional right after
graduating with a master’s degree in business administration from Strayer University. After the
monthly staff meeting, you were handed a new assignment by the company CEO. The assignment
came out of a discussion at the meeting in which one of Regional's clients wanted a report
describing the calls being handled for them by Regional. The CEO had asked you to describe the
data in a file called Regional Call Center and produce a report that would both graphically and
numerically analyze the data. The data are for a sample of 57 calls and for the following variables:
Account Number.
Past Due Amount.
Current Account Balance.
Nature of Call (Billing Question or Other).
Instructions
1. Summarize the case scenario of the Regional Call Center's Washington, D.C. facility.
2. Develop bar charts showing the mean and median current account balance.
3. Construct a scatter diagram showing current balance on the horizontal axis and past due amount
on the vertical axis.
4. Compute the key descriptive statistics for current and past due amount.
5. Repeat task 4 but compute the statistics for the past due balances.
6. Compute the coefficient of variation for current account balances.
7. Write a 4–5-page report (including a cover page and a source list page) to National’s client that
contains the results of the completed tasks along with a discussion of the statistics and graphs.
This course requires the use of Strayer Writing Standards. For assistance and information, please
refer to the Strayer Writing Standards link in the left-hand menu of your course. Check with your
professor for any additional instructions.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
The specific course learning outcome associated with this assignment is:
Apply strategies that are informed by the principles of statistical thinking and data-driven
decision making to enhance business process performance.
Scoring Guide
Summarize the case scenario including relevant tasks. 10 %
Unacceptable
Does not summarize
the case scenario
including relevant
tasks.
Needs Improvement
Describes the case
scenario without
relevant tasks.
Competent
Describes the case
scenario but missing
some tasks.
Exemplary
Summarizes the case
scenario including
relevant tasks.
Develop bar charts showing the mean and median current account balance. 15 %
Unacceptable
Does not develop bar
charts showing the
mean and median
current account
balance.
Needs Improvement
Presents inaccurate
bar charts for either
the mean or median
for current balance
account.
Competent
Presents bar charts
for either the mean or
median for current
account balance.
Exemplary
Develops bar charts
for mean and median
current balance
account.
Construct a scatter diagram showing current balance and past due amount on the correct axis. 15 %
Unacceptable
Does not construct a
scatter diagram
showing the current
balance and past due
amount on the correct
axis.
Needs Improvement
Produces inaccurately
the scatter plot for
both current balance
and past due amount.
Competent
Produces the scatter
plot for both current
balance and past due
amount values, but
with the wrong axis.
Exemplary
Constructs a scatter
diagram showing
current balance and
past due amount on
the correct axis.
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information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Compute key descriptive statistics for current and past due amount. 10 %
Unacceptable
Does not compute key
descriptive statistics
for current and past
due amount.
Needs Improvement
Calculates
inaccurately key
descriptive statistics
for current and past
due amount.s.
Competent
Determines some
descriptive statistics
for current and past
due amount.
Exemplary
Computes key
descriptive statistics
for current and past
due amount.
Compute key descriptive statistics for the past due balance. 10 %
Unacceptable
Does not compute key
descriptive statistics
for the past due
balance.
Needs Improvement
Calculates
inaccurately key
descriptive statistics
for the past due
balance.
Competent
Determines some
descriptive statistics
for the past due
balance.
Exemplary
Computes key
descriptive statistics
for the past due
balance.
Compute the coefficient of variation for current account balances. 10 %
Unacceptable
Does not compute the
coefficient of variation
for current account
balances
Needs Improvement
Calculates the
coefficient of variation
using the incorrect
account balance.
Competent
Determines the
coefficient of variation
with error for the
current account
balances.
Exemplary
Computes the
coefficient of variation
for current account
balances.
Generate analysis of the descriptive statistics, coefficient of variation, and graphs. 10 %
Unacceptable
Does not generate
analysis of the
descriptive statistics,
coefficient of variation,
and graphs.
Needs Improvement
Generates
inappropriate analysis
of the descriptive
statistics, coefficient
of variation, and
graphs.
Competent
Generates
appropriate analysis
of the descriptive
statistics or coefficient
of variation, or graphs.
Exemplary
Generates analysis of
the descriptive
statistics, coefficient
of variation, and
graphs.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Recommend, based on data analysis and graphs, two strategies to improve the service to the client. 10
%
Unacceptable
Does not recommend,
based on data
analysis and graphs,
two strategies to
improve the service to
the client.
Needs Improvement
Recommends, without
data analysis, two
strategies to improve
the service to the
client.
Competent
Recommends, based
on incorrect data
analysis, two
strategies to improve
the service to the
client.
Exemplary
Recommends, based
on data analysis and
graphs, two strategies
to improve the service
to the client.
Provide two quality resources. 5 %
Unacceptable
No references
provided.
Needs Improvement
Does not meet the
required number of
references; some or
all references are not
peer-reviewed,
academic references.
Competent
Meets the required
number of references;
some or all references
are not peer-
reviewed, academic
references.
Exemplary
Meets the required
number of references;
all references are
peer-reviewed,
academic references.
Writing contains accurate grammar, mechanics, and spelling in accordance with SWS style. 5 %
Unacceptable
Writing contains
excessive grammar,
mechanical, or
spelling errors that
impede the reading of
the assignment.
Needs Improvement
Writing contains 3–5
grammar, mechanical,
and/or spelling errors.
Competent
Writing contains 1–2
grammar, mechanical,
and/or spelling errors.
Exemplary
Writing contains no
grammar, mechanical,
and/or spelling errors.
Activity: Sampling Distribution
Summary
Click the linked activity title to access this activity.
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information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Text
A computer scanner can read a bar code on a package correctly 97% of the time. One company
monitors the accuracy of the scanner by randomly sampling packages and verifying that each
package has been correctly scanned. Random samples of size n = 25, 50, 100, and 200 have
recently been taken with the following results.
Sample Size, n Number Correctly Scanned
25 24
50 49
100 95
200 193
To complete this activity, use Excel to:
1. Calculate the sample proportion for each sample size.
2. Calculate the single-proportion sampling error for each sample size.
3. Calculate the probability of finding 198 correctly scanned packages, for a sample of size n=200.
Submit your Excel file.
Scoring Guide
Calculate the sample proportion for each sample size. 34 %
Unacceptable (Below
70%)
Does not calculate the
sample proportion for
each sample size.
Needs Improvement (70-
79%)
Computes, incorrectly,
the sample proportion
for each sample size.
Competent (80-89%)
Computes the correct
sample proportion for
some, but not all, of
the sample size.
Exemplary (90-100%)
Calculates the sample
proportion for each
sample size.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Calculate the single-proportion sampling error for each sample size. 33 %
Unacceptable (Below
70%)
Does not calculate the
single-proportion
sampling error for
each sample size.
Needs Improvement (70-
79%)
Solves, inaccurately,
single-proportion
sampling error for
each sample size.
Competent (80-89%)
Calculates some
single-proportion
sampling errors for
each sample size.
Exemplary (90-100%)
Calculates the single-
proportion sampling
error for each sample
size.
Calculate the probability of finding 198 correctly scanned packages, for a sample of size n=200. 33 %
Unacceptable (Below
70%)
Does not calculate the
probability of finding
198 correctly scanned
packages, for a
sample of size n=200.
Needs Improvement (70-
79%)
Solves, inaccurately,
the probability of
finding 198 correctly
scanned packages,
for a sample of size
n=200.
Competent (80-89%)
Calculates the
probability of finding
198 correctly scanned
packages, with an
incorrect proportion.
Exemplary (90-100%)
Calculates the
probability of finding
198 correctly scanned
packages, for a
sample of size n=200.
Activity: Hypothesis Testing
Summary
Click the linked activity title to access this activity.
Text
The Lazer Company has a contract to produce a part for Boeing Corporation that must have an
average diameter of 6 inches and a standard deviation of 0.10 inch. The Lazer Company has
developed a process that will meet the specifications with respect to the standard deviation, but it is
still trying to meet the mean specifications. A test run (considered a random sample) of parts was
produced, and the company wishes to determine whether this latest process that produced the
sample will produce parts meeting the requirement of an average diameter equal to 6 inches.
Use Excel to:
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information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
1. Construct the appropriate null and alternative hypotheses with correct parameters.
2. Develop the decision rule assuming that the sample size is 200 parts and the significance level is
0.01.
In a Word document:
Recommend what the Lazer Company should conclude if the sample mean diameter for the
200 parts is 6.03 inches.
Submit your recommendations in a Word document and attach your Excel file.
Scoring Guide
Construct the appropriate null and alternative hypotheses with correct parameters. 34 %
Unacceptable (Below
70%)
Does not construct
the appropriate null
and alternative
hypotheses with
correct parameters.
Needs Improvement (70-
79%)
Constructs the null
and alternative
hypotheses using
incorrect parameters.
Competent (80-89%)
Constructs the null
and alternative
hypotheses using an
incorrect population
parameter.
Exemplary (90-100%)
Constructs the
appropriate null and
alternative
hypotheses with
correct parameters.
Develop the decision rule and the significance level. 33 %
Unacceptable (Below
70%)
Does not develop the
decision rule and the
significance level.
Needs Improvement (70-
79%)
Develops the
incorrect decision rule
and the incorrect
significance level.
Competent (80-89%)
Develops the decision
rule and the incorrect
significance level.
Exemplary (90-100%)
Develops the decision
rule and the
significance level.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Recommend what the Lazer Company should conclude if the sample mean diameter for the 200 parts
is 6.03 inches. 33 %
Unacceptable (Below
70%)
Does not recommend
what the Lazer
Company should
conclude if the sample
mean diameter for the
200 parts is 6.03
inches.
Needs Improvement (70-
79%)
Identifies solutions the
Lazer Company
should take if the
sample mean
diameter for the 200
parts is 6.03 inches.
Competent (80-89%)
Describes solutions
the Lazer Company
should take if the
sample mean
diameter for the 200
parts is 6.03 inches.
Exemplary (90-100%)
Recommends what
the Lazer Company
should conclude if the
sample mean
diameter for the 200
parts is 6.03 inches.
Week 8 Assignment - Case Study: Statistical Inference
Summary
Click the linked activity title to access this assignment.
Text
Overview
The research department of an appliance manufacturing firm has developed a new bimetallic
thermal sensor for its toaster. The new bimetallic thermal sensor can sense the temperature of the
bread and move the lever arm to activate the switch. The research department claims that the new
bimetallic thermal sensor will reduce appliance returns under the one-year full warranty by 2%–6%.
To determine if the claim can be supported, the testing department selects a group of the toasters
manufactured with the new bimetallic thermal sensor and a group with the old thermal sensor and
subjects them to a normal year’s worth of wear. Out of 250 toasters tested with the new bimetallic
thermal sensor, 8 would have been returned. Seventeen would have been returned out of the 250
toasters with the old thermal sensor. As the manager of the appliance manufacturing process, use a
statistical procedure to verify or refute the research department’s claim.
Instructions
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information and may not be c
opied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Create 8–10 slides, including a cover and a sources list, for a presentation to the director of the
manufacturing plant in which you:
1. Summarize the problem with the appliance manufacturing firm's toaster.
2. Propose the statistical inference to use to solve the problem. Support your decision using a
scholarly reference.
3. Using Excel:
Develop a flowchart for the proposed statistical inference, including specific steps.
Compute all statistical calculations using Excel.
4. Place your flowchart in a slide.
5. Determine if you can verify or refute the research department's claim.
6. Choose sources that are credible, relevant, and appropriate. Cite each source listed on your
source page at least one time within your assignment. For help with research, writing, and
citation, access the library or review library guides.
This course requires the use of Strayer Writing Standards. For assistance and information, please
refer to the Strayer Writing Standards link in the left-hand menu of your course. Check with your
professor for any additional instructions.
The specific course learning outcome associated with this assignment is:
Develop recommendations to improve business processes using statistical tools and analysis.
Scoring Guide
Summarize the problem with the appliance manufacturing firm’s blenders. 18 %
Unacceptable
Does not summarize
the problem with the
appliance
manufacturing firm’s
blenders.
Needs Improvement
Identifies the problem
with the appliance
manufacturing firm’s
blenders.
Competent
Describes the
problem with the
appliance
manufacturing firm’s
blenders.
Exemplary
Summarizes the
problem with the
appliance
manufacturing firm’s
blenders.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Propose the statistical inference to use to solve the problem. 18 %
Unacceptable
Does not propose the
statistical inference to
use to solve the
problem.
Needs Improvement
Selects the incorrect
statistical inference to
use to solve the
problem.
Competent
Selects the correct
statistical inference
using incorrect
parameters.
Exemplary
Proposes the
statistical inference to
use to solve the
problem.
Develop a flowchart for the proposed statistical inference, including specific steps. 18 %
Unacceptable
Does not develop a
flowchart for the
proposed statistical
inference, including
specific steps.
Needs Improvement
Presents an
inaccurate flowchart
for the proposed
statistical inference
without including
specific steps.
Competent
Creates a flowchart
for the proposed
statistical inference
without including
specific steps.
Exemplary
Develops a flowchart
for the proposed
statistical inference,
including specific
steps.
Compute all statistics calculations using Excel. 18 %
Unacceptable
Does not compute all
statistics calculations
using Excel.
Needs Improvement
Solves, inaccurately,
statistics calculations
using Excel.
Competent
Calculates some
statistics calculations
using Excel.
Exemplary
Computes all
statistics calculations
using Excel.
Determine if one can verify or refute the research department’s claim. 18 %
Unacceptable
Does not determine if
one can verify or
refute the research
department’s claim.
Needs Improvement
Identifies the need to
verify or refute the
research
department’s claim.
Competent
Describes how one
might verify or refute
the research
department’s claim.
Exemplary
Determines if one can
verify or refute the
research
department’s claim.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Provide three quality resources. 5 %
Unacceptable
No references
provided.
Needs Improvement
Does not meet the
required number of
references; some or
all references are not
peer-reviewed,
academic references.
Competent
Meets the required
number of references;
some or all references
are not peer-
reviewed, academic
references.
Exemplary
Meets the required
number of references;
all references are
peer-reviewed,
academic references.
Writing contains accurate grammar, mechanics, and spelling in accordance with SWS style. 5 %
Unacceptable
Contains excessive
grammar, mechanics,
or spelling errors that
impede the reading of
the assignment.
Needs Improvement
Contains 3–5
grammar, mechanics,
and/or spelling errors.
Competent
Contains 1–2
grammar, mechanics,
and/or spelling errors.
Exemplary
Writing contains no
grammar, mechanics,
and/or spelling errors.
Activity: Linear Regression Analysis
Summary
Click the linked activity title to access this activity.
Text
Terry Downes owns a commercial cleaning company. He has conducted a survey of customers to
determine how satisfied they are with the work performed. He devised a 100-point rating scale—with
0 being poor and 100 being excellent service, selected a random sample of 14 customers, and
asked them to rate the service. He also recorded the number of worker hours spent in the
customer's facility. These are in the file named Downes.
Use Excel to complete the following:
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
1. Develop a scatter plot showing the variables, rate of service and worker hours, with the y variable
on the vertical axis and the x variable on the horizontal axis, and indicating the type of
relationship.
2. Develop a linear regression model to explain the variation in the service rating.
Use Word to complete the following:
1. Describe the model, showing the results of pertinent hypothesis tests, using a significance level of
0.10.
Submit your work in a Word document and attach your Excel file.
Scoring Guide
Develop a scatter plot showing the variables, rate of service and worker hours, with the y variable on
the vertical axis and the x variable on the horizontal axis, including the type of relationship. 34 %
Unacceptable (Below
70%)
Does not describe a
scatter plot showing
the variables, rate of
service and worker
hours, or their
relationship.
Needs Improvement (70-
79%)
Describes a scatter
plot showing the
variables, rate of
service and worker
hours, but with errors
related to the axes
and relationships.
Competent (80-89%)
Develops a scatter
plot showing the
variables, rate of
service and worker
hours, but with errors
related to the axes
and relationships.
Exemplary (90-100%)
Develops a scatter
plot showing the
variables, rate of
service and worker
hours, with the y
variable on the
vertical axis and the x
variable on the
horizontal axis,
including the type of
relationship.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
Develop a linear regression model to explain the variation in the service rating. 33 %
Unacceptable (Below
70%)
Does not develop a
linear regression
model to explain the
variation in the service
rating.
Needs Improvement (70-
79%)
Identifies a linear
regression model to
explain the variation in
the service rating.
Competent (80-89%)
Describes a linear
regression model to
explain the variation in
the service rating.
Exemplary (90-100%)
Develops a linear
regression model to
explain the variation in
the service rating.
Describe the model, showing the results of pertinent hypothesis tests, using a significance level of
0.10. 33 %
Unacceptable (Below
70%)
Does not identify a
model.
Needs Improvement (70-
79%)
Identifies a model,
showing the results of
incorrect hypothesis
tests.
Competent (80-89%)
Describes a model
that shows the results
of pertinent
hypothesis tests, but
using a significance
level of other than
0.10.
Exemplary (90-100%)
Describes the model,
showing the results of
pertinent hypothesis
tests, using a
significance level of
0.10.
Activity: Multiple Regression Analysis
Summary
Click the linked activity title to access this activity.
Text
Amazon.com has become one of the most successful online merchants. Two measures of its
success are sales and net income/loss figures. The data can be found in the file, Amazon.
Use Excel to complete the following:
1. Construct a scatter plot for Amazon's net income/loss and sales figures for the period 1995–2015.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be co
pied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
2. Determine a polynomial model, including its order (or degree), for Amazon's net income/loss and
sales figures.
Use Word to complete the following:
1. Explain your process of determining the polynomial model.
Submit your work in a Word document and attach your Excel file.
Scoring Guide
Construct a scatter plot for Amazon’s net income/loss and sales figures. 50 %
Unacceptable (Below
70%)
Does not construct a
scatter plot for
Amazon’s net
income/loss and sales
figures.
Needs Improvement (70-
79%)
Constructs a scatter
plot for Amazon’s net
income/loss, but
excludes the sales
figures and has other
errors.
Competent (80-89%)
Constructs a scatter
plot for Amazon’s net
income/loss and sales
figures, but with
errors.
Exemplary (90-100%)
Constructs a scatter
plot for Amazon’s net
income/loss and sales
figures.
Determine a polynomial model, including its order (or degree), for Amazon's net income/loss and sales
figures. 50 %
Unacceptable (Below
70%)
Does not determine a
polynomial model,
including its order (or
degree), for Amazon's
net income/loss and
sales figures.
Needs Improvement (70-
79%)
Determines,
incorrectly, the
polynomial model,
including its order (or
degree), for Amazon's
net income/loss and
sales figures.
Competent (80-89%)
Determines the
polynomial model as
indicated by the
Amazon data, but
incorrectly identified
the order (or degree).
Exemplary (90-100%)
Determines a
polynomial model,
including its order (or
degree), for Amazon's
net income/loss and
sales figures.
2020 Strayer University. All Rights Reserved. This document contains Strayer University Confidential and Proprietary
information and may not be copied, further distributed, or otherwise disclosed in whole or in part, without the expressed written
permission of Strayer University.
2022 Strategic Education, Inc., Version 3
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